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Peters and Västfjäll 1 Affective Processes in Decision Making
Affective Processes in Decision Making by Older Adults
Ellen Peters and Daniel Västfjäll
The rate of increase in the older adult population is "unprecedented, without parallel in
human history—and the twenty-first century will witness even more rapid aging than did the
century just past" (United Nations, 2005). By 2050 the number of older persons (60 years and
older) will surpass the number of younger persons (under age 15) for the first time in history.
The fastest growing age group in the world is the oldest old (age 80 and older). Given the
growth of the older adult population and the importance of judgment and decision processes to
independent functioning in everyday life, understanding the mechanisms that underlie the
judgments and decisions of older adults can help us to identify decision situations where they
may be vulnerable and ways in which their decisions may be helped. Although early research
pointed towards improvements in everyday problem solving with age (Cornelius & Caspi, 1987),
a recent meta-analytic review suggests that, in general, decision quality declines from
early/middle adulthood (these groups showed equivalent problem solving) to late adulthood
(Thornton & Dumke, 2005). This age difference was substantially less in interpersonal compared
to instrumental domains and for highly educated older adults.
Historically, judgment and decision making research focused primarily on explanations
that involved conscious, deliberative processing of information (e.g., reason-based choice, Shafir
Simonson, & Tversky, 1993). More recent research (conducted primarily with younger adults)
has highlighted the importance of affective and emotional processes in decision making. In both
historical and more recent research, studies involving older-adult subjects are quite sparse, with
researchers focusing their efforts on how younger adults (and usually college sophomores) judge
and decide. Some recent reviews have started to examine this sparse literature (Mather, in press;
Peters et al., 2000; Peters, Hess, Auman, & Västfjäll, in preparation; Yates et al., 1999).
In this paper we review evidence for the role of affect in younger-adult decision making,
review two representative life-span theories with relevant predictions for older adult decisions,
and then review available evidence (guided by predictions from life-span theories) of how older
adults make decisions by experience and decisions by description.
Peters and Västfjäll 2 Affective Processes in Decision Making
Affect and Emotion in Decision Making By Younger Adults
Information in decision making appears to be processed using two different modes of
thinking: affective/experiential and deliberative (Epstein, 1994; Loewenstein et al., 2001; Reyna,
2004; Sloman, 1996; also called System 1 and 2, respectively, Stanovich & West, 2002;
Kahneman, 2003). Both modes of thought are important to forming decisions. The experiential
mode produces thoughts and feelings in a relatively effortless and spontaneous manner. The
operations of this mode are implicit, intuitive, automatic, associative, and fast. This system is
based on affective (emotional) feelings, and one of its primary functions is to highlight
information important enough to warrant further consideration. As shown in a number of studies,
these affective feelings provide both meaning and motivation to choice processes (Damasio,
1994).
The deliberative mode is conscious, analytical, reason-based, verbal, and relatively slow.
It is the deliberative mode of thinking that is more flexible and provides effortful control over
more spontaneous experiential processes. Kahneman (2003) suggests that one of the functions of
this system is to monitor the quality of information processing and its impact on behavior (e.g.,
from the experiential mode). Both modes of thinking are important and good choices are most
likely to emerge when affective and deliberative modes work in concert and decision makers
think as well as feel their way through judgments and decisions (Damasio, 1994).
In the present paper we focus mostly on the role of affect, but we consider deliberative
(System 2) influences as well because of the interdependence of the two systems. Affect can help
or hurt the quality of decisions, depending on the situation. It can be relevant to the decision at
hand (e.g., your feelings about circuses have been learned through repeated experiences), in
which case it is termed integral affect. Integral affect is defined as positive and negative feelings
towards an external stimulus (e.g., a consumer product). These feelings can become associated
with an object through careful thought, but also through experiential processes such as
conditioning (Staats & Staats, 1958), familiarity (Zajonc, 1980), priming (Murphy & Zajonc,
1993), and mood misattribution (Schwarz & Clore, 1983). Affect can also be irrelevant to a
decision (e.g., a temporary mood state), but influence the decision nonetheless; this affect is
termed incidental affect.
Peters and Västfjäll 3 Affective Processes in Decision Making
Integral Affect
In research with brain-damaged patients (Bechara, Damasio, Damasio, & Anderson,
1994; Bechara, Damasio, Tranel, & Damasio, 1997; Bechara, Tranel, Damasio, & Damasio,
1996; Damasio, 1994), Bechara and his colleagues linked the learning of integral affect to better
decision making. Patients with bilateral damage to the ventromedial prefrontal cortices
experienced normal affective reactions to gains and losses they received from decks of cards.
However, unlike the normal controls, the patients were unable to use these affective experiences
to learn an integral affective response linked to each deck (Bechara and colleagues call the
integral affective response “somatic markers”). Among non-brain-damaged control subjects,
affective reactions to actual gains and losses in each deck appeared to drive the learning of an
anticipatory affective response (an integral affective response or somatic marker) that
subsequently guided choices. Bechara and colleagues concluded that this anticipatory affective
response must drive choice because the patients demonstrated abnormal affective anticipatory
reactions but normal cognitive capabilities. Peters and Slovic (2000) demonstrated that college
students high in negative reactivity learned to choose fewer high-loss options in a modified Iowa
Gambling Task while those high in positive reactivity learned to choose more high-gain options,
thus supporting the notion that affective reactions are used in the decision-making process.
Damasio (1994) argued that anticipatory affective responses increase the accuracy and efficiency
of the decision process, and their absence (e.g., in the brain-damaged patients) degrades decision
performance.
This reliance on affect may be learned over the life span as a particularly effective means
of making decisions. Reyna (2004), for example, argues that information processing in this
system is more advanced relative to the deliberative system. In support of this idea, she provides
evidence that people process less information more qualitatively as development progresses from
childhood to adulthood and from less expertise to more.
Decision makers rely on affective meaning to guide judgments and decisions in everyday
life (Slovic, Finucane, Peters, & MacGregor, 2002). According to the “affect heuristic”, all of
the images in a person’s mind are tagged or marked to varying degrees with affect. The “affect
pool” contains all positive and negative markers that are consciously or unconsciously associated
with the images. Using this overall, readily available affective impression can be easier and
Peters and Västfjäll 4 Affective Processes in Decision Making
more efficient than weighing the pros and cons of a situation or retrieving relevant examples
from memory. This may be especially true when the required judgment or decision is complex or
mental resources are limited as with time pressure (Finucane, Alhakami, Slovic, & Johnson,
2000).
Integral affect has at least four functions in the decision-making process (Peters, in press;
Peters, Lipkus, & Diefenbach, in press). First, it can act as information (as a substitute for other,
more relevant information; Kahneman, 2003) in judgments such as life satisfaction (Schwarz &
Clore, 1983). Second, it can act as a common currency allowing us to integrate multiple pieces
of information more effectively than when it is absent. Third, it can act as a spotlight focusing us
on different information — numerical cues, for example; this new information is then used in
judgments rather than the affect itself. Finally, affect can motivate us to take some action or
process information.
Affect can be a "direct hit" when the decision maker is familiar with the object (e.g., a
somatic marker learned through experience, a reaction to a snake or a familiar smell from
childhood, a picture of an old friend). According to Zajonc (1980), all perceptions contain some
affect. “We do not just see ‘a house’: We see a handsome house, an ugly house, or a pretentious
house” (p. 154). He later adds, “We sometimes delude ourselves that we proceed in a rational
manner and weight all the pros and cons of the various alternatives. But this is probably seldom
the actual case. Quite often ‘I decided in favor of X’ is no more than ‘I liked X’ . . . We buy the
cars we ‘like,’ choose the jobs and houses we find ‘attractive,’ and then justify these choices by
various reasons . . . “(p. 155).
Affect also, however, can be calculated through deliberation. In a series of studies with
younger adults, Peters, Västfjäll, et al. (in press) examined the role of numeracy or number
ability in decision making. They found that highly numerate individuals were able to draw more
and more precise affective meaning from numbers and numerical comparisons. While generally
helpful, this sometimes leads to worse judgments. The less numerate were influenced more by
competing, irrelevant affective considerations (they were more influenced by affect as a direct
hit). Even after controlling for a measure of intelligence, actual numerical ability appeared to
matter to judgments and decisions in important ways. The high numerate were able to transform
numbers from a given numerical format to an equivalent one; they were also able to "calculate"
Peters and Västfjäll 5 Affective Processes in Decision Making
affective reactions from numbers in ways that influenced their decisions. The low numerate
appeared to be left with information that was less complete and less understood, lacking in the
complexity and richness available to the more numerate. Older adults have less numerical ability
in pilot studies we have conducted thus far. If Paulos (1988) is correct, then older adults' greater
innumeracy may result in confused personal decisions and an increased susceptibility to
pseudoscience. This is an open research question, however.
Affective meaning can also be drawn from how information is represented. Hsee (1998)
found that an overfilled ice cream container with 7 oz. of ice cream was valued more highly
(measured by willingness to pay) than an underfilled container with 8 oz. of ice cream when the
options were evaluated separately. This “less is better effect” reversed when the options were
juxtaposed and evaluated together. Thus, the proportion of the serving cup that was filled ap-
peared to be more evaluable (in separate judgments) than the absolute amount of ice cream.
Using the “evaluability” principle, Peters, Västfjäll, Slovic, and Hibbard (in preparation)
examined whether highlighting the affective significance of information would influence the
health-plan choices of older adults more than younger adults. In an initial study, younger and
older adults were presented with identical attribute information (quality of care and member
satisfaction) about two health plans. The information was presented in bar chart format with the
actual score displayed to the right of the bar chart. The information for half of the subjects in
each group was supplemented by the addition of affective categories (i.e., the health plans could
be categorized as poor, fair, good, or excellent on the basis of these categories). The attribute
information was designed such that Plan A was good on both attributes while Plan B was good
on quality of care but fair on member satisfaction. The specific scores for quality of care and
member satisfaction were counterbalanced across subjects such that, for half of the subjects, the
average quality of care scores were higher; for the other half, average member satisfaction scores
were higher. It was found that affective categories influenced the choices of older adults but not
younger adults. Specifically, older adults preferred health plan A more often when the categories
were present (plan A was always in the good affective category when the categories were
present). Affective categories did not significantly impact choices among younger adults. It
appeared that younger adults (and older adults higher in speed of processing) could “calculate”
affective meaning from the numbers on their own so that the affective-categories manipulation
impacted their choices very little.
Peters and Västfjäll 6 Affective Processes in Decision Making
Incidental Affect Including Mood
A substantial body of research suggests that affect which is incidental or unrelated to the
target or option under consideration (e.g., a positive or negative mood or an affective prime) can
have systematic effects on many everyday judgments and decisions that are similar to three of
the four functions of integral affect reviewed above (Forgas, 1995; Schwarz, 2001). In general,
three broad categories concerning how mood influences decision making have been identified in
younger-adult populations (Raghunathan & Pham, 1999). First, current mood may influence the
content of people’s thoughts in a mood-congruent manner (Bower, 1981; Wright & Bower,
1992). For instance, participants in a positive mood may more easily recall positive memories,
while negative-mood participants more easily recall negative memories (Forgas, 1995); this is
similar to integral affect's role as a spotlight that shows different moods will highlight different
information. Second and similar to integral affect's role as a motivator, research has shown that
positive and negative moods may influence behavioral predispositions and motives for action
(Raghunathan & Pham, 1999) or processing capabilities (Luce, Bettman, & Payne, 1997). For
instance, happy individuals often tend to process information in a less elaborated and systematic
manner than do people in a negative mood (Isen, 2000). Happy people also tend to be more
creative and efficient in their decisions (Isen, 2000; Mano, 1992; Forgas, 1995). In general,
happy individuals may avoid negative events and outcomes in order to maintain their positive
mood state (Isen, 2000). Other research suggests that positive mood may be used as a resource or
psychological buffer to cope with self-relevant negative information (Raghunathan & Trope,
2002). This appears to be a specific variant of the function of affect as a motivator proposed by
Peters (in press), in which positive affect may motivate approaching a specific goal such as a
necessary but difficult task or a tough choice. Finally, the mood-as-information view assumes
that when people make evaluative judgments they do not consult all available information but,
instead, rely on their affective reaction to the object (Clore et al., 2001; Schwarz, 2001). People
ask themselves “how do I like the object?” and, while doing so, monitor their own feelings.
Current mood may then be misattributed as integral affect to the target and used as information
in evaluative judgment.
Affect, whether integral or incidental to the decision target, appears to have a profound
effect—both deep and subtle—on judgments and choices. Decision makers are not necessarily
aware of, nor able to control, its influence on thoughts or behaviors.
Peters and Västfjäll 7 Affective Processes in Decision Making
Although affective and deliberative processes in decision making are interdependent as
can be seen in the functions of affect and the work on numeracy and decision making, they also
appear to be separable (e.g., Epstein, 1994; Petty & Wegener, 1999; Zajonc, 1980). While the
hallmark of good decision making is generally believed to be one of increasing deliberation (if I
can only think for longer or better, then I could make a better decision), deliberation in some
contexts appears to distract decision makers from fully considering their feelings and to have a
negative effect on decision processes (e.g., Wilson, Dunn, Kraft, & Lisle, 1989). Research has
also demonstrated that affect may have a relatively greater influence when deliberative capacity
is lower, suggesting that, at least in some cases, these two modes are not separate but instead
exist on a single continuum (Hammond, 1996; Kruglanski, Chun, Erb, Pierro, Mannetti, &
Spiegel, 2003). Shiv and Fedorikhin (1999), for example, demonstrated that decision makers
were more likely to choose an affect-rich option (and make a decision of the heart) when
deliberative capacity was diminished by cognitive load. Finucane et al. (2000) also found that
the inverse relation between risks and benefits (linked to affect by Alhakami and Slovic, 1994)
was enhanced under time pressure. Reducing the time for deliberation appeared to increase the
use of affect and the affect heuristic. We link this balance between affect and deliberation to age
differences in information processing and decision making in the next sections.
The Construction Of Preferences
The construction of preferences occurs with input from both the affective and deliberative
systems. How individuals make decisions (what decision strategies they select to use) and what
they choose is highly contingent on the properties of the decision problem and on characteristics
of the individual decision maker at the moment of the decision (cognitive and affective abilities,
stable personality traits, more ephemeral moods). In the next section, we will briefly review two
life span theories that are related to how older versus younger adults might process information
in decisions.
Processing of Affective and Emotional Information across the Life Span
Prominent life-span theories associate adult aging with the continued development of
cognitive and motivational processes relevant to the processing of affective information in
judgments and decisions. There appears to be a complex interplay between cognitive
development, motivational changes, and aspects of the situation such as the extent of arousal and
cognitive resources required. We review two life-span theories, socioemotional selection theory
Peters and Västfjäll 8 Affective Processes in Decision Making
(SST; Carstensen, 1993) and dynamic integration theory (DIT; Labouvie-Vief, 2005) that
represent theories based on motivational changes (SST) and cognitive decline (DIT).
Is Affect Resilient to or Enhanced by Aging?
It is generally accepted that aspects of deliberative processing (e.g., speed of processing,
performance on explicit tasks) decline with age just as the green color fades from the leaves of
trees in autumn. As a result, age differences should appear in judgments and decisions requiring
deliberation. The role of affect is somewhat less clear. Affect may be like the orange and yellow
colors of fall leaves. These colors “appear” strongly as the green fades; in actuality, the orange
and yellow colors are mostly unchanged from earlier in the season but are no longer hidden by
the green. Just as orange and yellow colors are resilient to the changing season, affect may be
resilient to the aging process such that no age differences will emerge on tasks that primarily
involve affect. Older adult decisions would be influenced more than those of younger adults,
however, on tasks involving both affect and deliberation because affect may become relatively
more influential as deliberative abilities decline. This hypothesis is consistent with Labouvie-
Vief's dynamic integration theory. See the upper half of Figure 1 for a simplified illustration of
this resiliency hypothesis.
A second possibility, consistent with an age-related increase in the importance of and
attention paid to affective information (SST; Carstensen, Isaacowitz, & Charles, 1999), is that
affect’s influence on judgments and decisions may increase with age (this simplified
enhancement hypothesis is shown in the lower half of Figure 1). Socioemotional selectivity
theory predicts that aging leads to motivational shifts that direct attention to emotional goals and
thus to a greater monitoring of emotional information. The hypothesized enhancement process is
analogous to the red color that develops from the glucose in autumn tree leaves.
Both theories leave open the possibility that the processing of positive information may
be relatively more enhanced while that of negative information remains stable or declines with
age.
This analysis assumes affect as a direct hit. In other words, affect is associated with an
object based on previous learning. Then, when considering the object, the affective reaction is
elicited (e.g., a somatic marker) and influences judgments and decisions in a relatively direct
Peters and Västfjäll 9 Affective Processes in Decision Making
way. As pointed out in the earlier discussion on numeracy, affect can also be calculated, for
example, through a comparison of numbers. No published studies exist, to the best of our
knowledge, about this aspect of affective processing across the life span. As a result, we will
focus on the role of affect and emotions as a direct hit in judgments and decisions in this paper.
Socioemotional Selectivity Theory
Carstensen (1993) posits in her socioemotional selectivity theory (SST) that emotional
goals become increasingly important as the end of life nears due to motivational shifts that direct
attention to these emotional goals and thus to a greater monitoring of affective information.
Because older adults are, by virtue of age, closer to the end of life, then age should be associated
with an increased importance of emotional goals, increased attention to emotional content, and
an increased focus on positive information that can be used to optimize emotional experience.
These latter two predictions potentially have great relevance to the impact of affect and emotions
in judgment and decision making.
Recent empirical work has shown that aging is associated with an increase in attention to
emotional content. For example, Carstensen and Turk-Charles (1994) had adults in four different
age groups (20-29, 35-45, 53-67, and 70-83) read and recall stories containing both neutral and
emotion-laden content. Examination of the data revealed a linear decline across the four age
groups in recall of neutral content with age, but stability in recall of emotional content. Thus,
older adults recalled relatively more emotional content than neutral content, supporting their
contention that there was a shift in the nature of the memory representation toward
disproportionate retention of emotional information. Fung and Carstensen (2003) examined
memory for advertisements and found that older adults exhibited greater preference for the
emotional advertisements than did younger adults. In addition, memory for advertisements with
emotional appeals comprised a greater proportion of the total information remembered in older
adults compared to younger adults.
SST, however, also predicts a specific focus on positive information in later life as older
adults seek to optimize emotional experience. A recent fMRI study by Mather et al. (2004)
obtained findings consistent with this prediction. Specifically, older adults (compared to younger
adults) had disproportionately greater activation in the amygdala in response to positive versus
negative information, suggesting an age-related shift in processing styles. Several behavioral
Peters and Västfjäll 10 Affective Processes in Decision Making
studies of memory are also consistent with this expectation. For example, Charles, Mather, and
Carstensen (2003) found overall picture recall to decline with age, but older adults recalled a
greater proportion of positive images than negative images, while young and middle-aged adults
recalled similar amounts of each. Mather and Carstensen (2003) found that, relative to younger
adults, older adults exhibited a disproportionate attentional bias in favor of faces depicting
positive emotions over those depicting negative emotions. This attentional bias was also
reflected in their superior memory for positive faces over neutral or negative faces; no such
effect was observed for younger adults. Mather and Johnson (2000) also examined source
memory for positive and negative features of selected and unselected options in a decision-
making task (e.g., choosing between job candidates). They found that older adults were more
likely than young adults to have accurate memory for positive over negative features of the
selected options and negative over positive features of the unselected options. Importantly, this
aging-related bias was present when overall level of memory performance was controlled, and
younger adults exhibited a similar bias when asked to focus on the emotional content of their
choices. These findings suggest a motivational shift in processing rather than a deficiency in
deliberative processes. Similar age differences appear in incidental mood states. Older adults
tend to be in more positive and less negative mood states compared to younger adults (Mroczek,
2001). 1
Dynamic Integration Theory
According to Labouvie-Vief’s (2003) dynamic integration theory of adult development,
these same effects are explained by age changes in a dynamic balance between processes of
affect optimization (of happiness) and affect differentiation (the ability to tolerate negativity in
order to maintain objective representations). The positivity bias is explained as a reflection of an
age-related limitation in cognitive resources with an adaptive shift to less resource-demanding
positive affect rather than a motivational change as Carstensen suggests. The focus on positive 1 It may be, however, that the effects found by Carstensen and colleagues are based in controlled processing of affective information rather than qualitative changes in cortical structures associated with aging. For example, the positivity biases in memory observed in older adults tend to occur only in situations where participants are not required to attend to all stimuli. In such cases, older adults appear to focus on positive and ignore negative information. When participants are required to process each piece of information presented to them, no age differences emerge in the impact of valence on memory (e.g., Comblain, D’Argembeau, Van der Lindin, & Aldenhoff, 2004; Denburg, Buchanan, Tranel, & Adolphs, 2003; Kensinger, Brierly, Medford, Growdon, & Corkin, 2002). Mather et al. (2004), however, reported reduced amygdala activation in older adults while viewing negative images, implicating early attentional processes that require few resources.
Peters and Västfjäll 11 Affective Processes in Decision Making
emotional information may minimize demands on resources (Gross et al., 1997). Negative
emotions (e.g., anger, frustration) are energy and resource consuming (Mroczek & Kolarz, 1998)
and older adults’ declining cognitive resources may lead to a gating out of negative information
and other sources of negative emotion. This same cognitive decline is also used to explain an
age-related increase in the disruptive influence of emotionally arousing stimuli and thus the
increased attention to emotional content and other automated processes and the degradation of
complex representations. Wurm, Labouvie-Vief, Aycock, Rebucal, and Koch (2004), for
example, found that the higher the emotional arousal of words, the longer it took older adults to
indicate the color of the words; no such effect was found for younger adults.
Application and Ambiguities of Life-Span Theories to Decision Making
Given what we know about changes in information processing across the life span, what
predictions can we make and what ambiguities remain? The first prediction would be that
emotional information in some form will matter more in the judgments and decisions of older
adults compared to those of younger adults. The second prediction is that, if an age-related effect
exists, it will be due either to a motivational shift or to cognitive decline. The similarities and
differences between these lifespan theories leave us with two ambiguities, however.
First, under what conditions will a positivity effect emerge with age as opposed to a
greater general influence of affect? Wurm et al. (2004) suggest that valence and a positivity
effect may emerge in tasks that are less resource demanding so that attention can be directed to
valence.2 In their studies, older adults (but not younger adults) showed a larger Stroop effect for
emotion words that were higher in arousal. In other words, older adults took longer to name the
color of high arousal emotion words compared to low arousal emotion words; younger adults
showed no such arousal effect. The age effect was similar for both positive and negative words,
and they suggested that this may be due to a task design that required significantly more
cognitive resources compared to previous studies that did find a valence effect (but LeClerc &
Hess, 2004, found no age differences in a similar Stroop task). Wurm et al. also suggested,
however, that the positivity bias found in previous studies (e.g., Charles et al., 2003) may be due
to the negative stimuli being higher in arousal compared to the positive stimuli so that older
2 Mather et al. (2004), however, reported reduced amygdala activation in older adults while viewing negative images, implicating early attentional processes that require few resources.
Peters and Västfjäll 12 Affective Processes in Decision Making
adults gated out the negative stimuli. More empirical tests are needed to identify conditions
consistent with a positivity bias versus a more general influence of affect arousal.
The second ambiguity concerns whether these effects are due to improved emotional
regulation with age and an increased focus on emotional goals or to cognitive decline with aging
and a disintegration of emotion regulation that results in a dampening of negative affect and a
maximization of positive affect. According to SST, it is the perception of time left in life that
causes future concerns to decline in importance while goals concerning emotional satisfaction
and meaning become more important. These goals then are linked to greater emphasis on
emotional dimensions and a positivity bias in older adults, younger adults under experimental
conditions in which time is limited, and younger adults who are facing the end of their lives. The
emotional focus disappeared in older adults asked to imagine an expansive future (Mather &
Carstensen, 2003; Fung, Carstensen, & Lutz, 1999; Carstensen & Fredrickson, 1998).
Affect optimization and differentiation in older adults (e.g., Labouvie-Vief & Márquez
González, 2004), however, predicts that the increased focus on emotional information and
positivity bias emerges instead from compensatory processes of cognitive decline. Wurm et al.
(2004), for example, found that more arousing information disrupted older adults’ performance
in Stroop tasks more than that of younger adults. Labouvie-Vief (2005) frames an important
hypothesis, specifically that “older adults should have difficulty dealing with highly arousing
information, especially if such information has not yet been integrated into well-established
schemas” (p. 200). In some decision situations stronger intensity affect and emotions may act
more like a cognitive load on older versus younger adults. In addition, declines in cognitive-
affective complexity in older adults were associated with increases in optimization strategies,
lending support to the compensatory explanation (Labouvie-Vief, Zhang, & Jain, 2003 as cited in
Labouvie-Vief & Márquez González, 2004). To adequately test this explanation though, one
would need to demonstrate that declines in the experience or processing of negative affect and
increases in that of positive affect were associated with declines in cognitive resources among
the elderly. Studies in neither tradition, however, have reported such a finding.
In sum, research suggests that aging is associated with a greater focus on emotional
content and (under some conditions) on positive over negative information. These processes are
consistent with SST and dynamic integration theory. They are also consistent with the selective
Peters and Västfjäll 13 Affective Processes in Decision Making
optimization with compensation (SOC) model of P.B. Baltes and colleagues (e.g., Baltes &
Baltes, 1990) that postulates that the developmentally relevant goal of efficient use of processing
resources results in older adults optimizing their best skills, in this case the processing of
emotional information. The responsible mechanism, however, is not clear.
Implications Of Age-Related Changes In The Role Of Affect And Emotions On Decisions
A preference for positive information or increased use of affective information has
marked implications for judgments and decision making. Older adults who focus relatively more
on positive emotional information may process gain versus loss information in decisions
differently than their younger counterparts who do not have this positive focus. As a result,
losses may not loom as large for older adults as has been demonstrated for younger adults
(Kahneman & Tversky, 1979). Older adults may be more likely to be in positive moods, states
that have been associated with greater engagement in schema-based processing and less specific,
bottom-up processing (e.g., Fiedler, 2001).
Alternatively, older adults may focus relatively more on emotional information overall
(both positive and negative information). Several effects on judgments and decisions might be
observed if this is the case. First, losses may loom equally large or larger for older adults than
younger adults as both positive and negative information are accentuated. In addition, more
affective sources of information such as anecdotal or hedonic (not utilitarian) information may
receive greater weight (Strange & Leung, 1999; Dhar & Wertenbroch, 2000). Consistent with
this, Blanchard-Fields finds that older adults focus more than younger adults on emotional
aspects of everyday problems (Blanchard-Fields, Chen, & Norris, 1997). Finally, incidental
sources of affect (positive and negative moods; positive and negative primes) may influence
older adults' judgments and decisions more than those of younger adults. An interesting study by
Caruso and Shafir (in press) demonstrated that merely considering one’s feelings impacts
choices. Younger adult participants asked to consider their mood were more likely to choose a
mood-relevant movie (a silly comedy) over a more highly rated dramatic movie, compared to
participants who had not thought about their feelings. SST suggests that older adults’ feelings are
more salient and accessible than younger adults’ feelings, which leads to the prediction that older
adults overall may rely more on emotional information when making choices. Thus, older adults
should make relatively more choices that are mood-relevant. This possibility remains to be
tested.
Peters and Västfjäll 14 Affective Processes in Decision Making
In the present paper we categorize types of judgment and decision tasks, analyze the
results of available age-difference studies with respect to whether the studies demonstrated
increases, decreases, or no changes in the relative weights of positive, negative, or emotional
information (both positive and negative) in judgments and decisions. Finally, we examine
whether the available evidence was more consistent with cognitive decline (Labouvie-Vief's
hypothesis), motivational changes (socioemotional selectivity theory), or neither. In many cases,
we find that interesting hypotheses exist concerning age differences in specific types of decisions
and decision processes without any relevant published studies.
Decisions By Experience
Aging-related changes might be different in choices learned from experience than in
choices that are merely described. Fisk and Rogers (2000), for example, reviewed evidence that
decisions in well-learned environments (e.g., driving) are preserved with age. Other studies have
demonstrated more consistent decisions for older compared to younger adults, particularly in
domains where both groups have expertise (Tentari, Osherson, Hasher, & May, 2001; Kim,
Goldstein, Hasher, & Zacks, in press). In an experiment with younger adults, Weber, Shafir, and
Blais (2004) hypothesized and found that the encoding and use of outcome and likelihood
information was different when decision options were merely described (as is common in most
studies of judgment and decision making) versus when option characteristics were learned
through experience. Decisions by experience have been linked to affective processes. One of a
large number of “dual-process” theorists, Seymour Epstein (1994) has observed:
“The experiential system is assumed to be intimately associated with the experience of
affect, . . . which refer[s] to subtle feelings of which people are often unaware. When a person
responds to an emotionally significant event . . . the experiential system automatically searches
its memory banks for related events, including their emotional accompaniments . . . If the
activated feelings are pleasant, they motivate actions and thoughts anticipated to reproduce the
feelings. If the feelings are unpleasant, they motivate actions and thoughts anticipated to avoid
the feelings.” (p. 716)
We should expect, therefore, to find larger age differences in decisions by experience,
either for positive events or for both positive and negative events. There is some evidence
against this prediction, however. A second finding supported in numerous studies with younger
Peters and Västfjäll 15 Affective Processes in Decision Making
adults is that less frequent events (e.g., a 10% chance of an event occurring) are overweighted
relative to their objective probability of occurrence and more frequent events are under-weighted
(Kahneman & Tversky, 1979). Hertwig, Barron, Weber, and Erev (2004) demonstrated that
younger adults did overweight less frequent events as expected in decisions by description;
however, they underweighted less frequent events in decisions by experience. This difference
was explained by chance fluctuations in encountering rare events in experience. Hertwig et al.
speculated that this may be due to working memory limitations and the forgetting of less
frequent events. Therefore, we expect that, compared to younger adults, older adults will
overweight affective events in decisions by description, but in decisions by experience the
presence of infrequent events will create alternative effects.
In the absence of infrequent events, life-span theories predict either a relative
overweighting of positive information (in which case positive options will be learned faster and
negative options will be learned slower and therefore both types will be chosen more often) or an
overweighting of emotional information in general, leading to superior learning and decisions
among affectively-charged stimuli. In a related study, Hess, Pullen, and McGee (1996) examined
adult age differences in the ability to learn about a prototypical group member from descriptions
of group members and nonmembers. Despite claims that “it is well established that older people
tend to learn more slowly than do younger ones” (Fisk & Warr, 1998, p.112), older adults
performed better than younger adults in abstracting a prototype based on affective information,
providing support for an overweighting of emotional information. The authors argued that the
greater controlled processing abilities of younger adults interfered with their ability to abstract
the affective information.
These findings suggest that in choice tasks that involve learning through experience,
emotional information should be more salient to older adults, thus improving their ability to
abstract and use it in choice despite cognitive declines. Evidence in favor of such an explanation
comes from studies examining performance using tasks such as the Iowa Gambling Task (IGT)
and other similar tasks (Damasio, 1994), where age differences are often observed to be absent
(e.g., MacPherson, Phillips, & Sala, 2002; Kovalchik, Camerer, Grether, Plott, & Allman, 2005;
however in Denberg, Tranel, & Bechara, 2005, a subset of older adults performed significantly
worse). In this task, subjects choose among decks of cards about which they initially know
nothing. The decks vary in the amounts and frequencies of gains and losses and in overall
Peters and Västfjäll 16 Affective Processes in Decision Making
expected value; subjects learn about the decks as they choose and receive feedback after each
choice. Performance in this task appears to be based more on implicit processes because normal
adults could make good choices prior to conscious awareness of what good and bad choices
were. Denberg et al. (2005) found that a subset of older adults made particularly poor choices,
but none of their cognitive measures could explain the difference between older adults who made
good and bad choices. In addition, individuals with superior memory and IQ did not show better
knowledge of the task constituents (Damasio, 1994). Peters (1998; Peters & Slovic, 2000) also
showed that performance on this task was based in part on affective processes by showing that
scores on self-report measures of affective reactivity were associated with choices made by
college-student participants in the original and modified versions of the task. Wood, Busemeyer,
Koling, Cox, and Davis (2005) found that older and younger adults performed equally well on
the original version of the gambling task but, using a theoretical decomposition of the task, that
younger adults relied more on memory processes while older adults relied more on an accurate
representation of gains and losses in the task. This suggests that the relative preservation of
affective processes in older adults enabled them to compensate for losses in deliberative
processes. In preliminary analyses Peters (in preparation) also found that older adults performed
at least as well as younger adults on her modified version of the task. Of great interest, in the
older adult group a positive correlation emerged between age and the number of selections from
the good (high expected value) decks. Specifically, the older of the old adults made more good
choices than the younger of the old adults overall and in the first 20 card selections, providing
some of the first evidence that an increased focus on affective information may improve choices
in some situations. Finally, older adults, once they have learned a payoff structure, appear to
perform less well than younger adults if that payoff structure changes unexpectedly, at least
when abstract gains and losses are used (Mell, Heakeren, Marschner, Wartenburg, Villringer, &
Reischies, 2005).
This same IGT-type task can be used to examine the negativity bias. Wood et al. (2005)
examined model parameters from their theoretical decomposition and concluded that older
adults, unlike the younger college students, did not show a negativity bias. Because gains and
losses are confounded in the original IGT, they could not base their conclusion on actual choices.
Using Peters and Slovic’s (2000) modified IGT that unconfounded gains from losses, Peters (in
Peters and Västfjäll 17 Affective Processes in Decision Making
preparation) found no age difference (between college students and older adults) in choices
among gains versus losses.
Decisions By Description
Probability. Recent decision research has demonstrated a neglect of probabilities for
affective outcomes (Rottenstreich & Hsee, 2001). If age differences exist such that older adults
weigh positive outcomes more, negative outcomes less, or all affective outcomes more, then we
may observe greater probability neglect for positive outcomes, less probability neglect for
negative outcomes, or more probability neglect for all affective outcomes, respectively.
Research on cautiousness and stereotypy that have involved actual rewards for behaviors
have shown no significant age differences in cautiousness (i.e., younger and older adults showed
similar risk taking throughout the task) or in overall performance (i.e., rewards gained; Okun &
Elias, 1977). For example, Okun and Elias (1977) had older and younger adults participate in a
vocabulary task that involved varying degrees of risk with a payoff structure that varied either
directly or inversely with risk. In contrast to prior research using constant payoff structures, the
results did not indicate that older adults were more cautious than young adults. Both age groups
were equally sensitive to the payoff structure and overall expected value. Similar results were
found in a more recent study in which both older and younger adults took fewer risks as the level
of risk increased in a card game of “21” (Dror, Katona, & Mungur, 1998). In decisions by
description (each deck is described to participants but no feedback is provided), older and
younger adults also learn probabilistic information equally well (Sanford, Griew, & O’Donnell,
1972; Chasseigne, Grau, Mullet, & Cama, 1999). Deakin, Aitken, Robbins, and Sahakian (2004)
found that older adults (compared to younger adults) bet less and showed less of a tendency to
bet more when the likelihood of winning was higher and the likelihood of losing was lower in
the Decision-Gamble Task (Rogers et al., 1999). While the Deakin et al. results are consistent
with greater probability neglect of affective outcomes among older adults, it was unclear whether
older adults’ slower processing speed may have played a role in creating this result. The bulk of
the research points towards no age differences in reactions to probability as the result of gains
and losses. However, with the exception of Okun and Elias (1977), real rewards and losses were
not used, and thus the experienced outcomes may have all been relatively nonaffective.
Peters and Västfjäll 18 Affective Processes in Decision Making
Value. Prospect Theory (Kahneman & Tversky, 1979) predicts that the processing of
information about probabilities and consequences does not follow normative economic theory
but is driven by perceptual and attentional mechanisms common to all individuals. It predicts
that decision options (or prospects) are evaluated in terms of subjective values and likelihoods.
The value function is used to describe behaviors ranging from diminishing marginal
consequences to the negativity bias or loss aversion (losses loom larger than the equivalent
gains) to framing effects. These predictions are illustrated in the S-shaped value function that is
concave in the domain of gains and convex (and steeper) in the domain of losses. Robust
findings with younger adults (illustrated by the S-shaped value function of Prospect Theory)
indicate that losses tend to loom larger than gains, a negativity bias. As a result, decision makers
tend to be more risk-seeking in choices among possible losses and risk averse when choosing
among possible gains. Findings consistent with lifespan theories suggest that the negativity bias
in older adults may be different from younger adults in any of three ways (Peters, Hess, et al., in
preparation).
First, the bias may be enhanced as emotional information in general becomes more
salient. In this case, Prospect Theory’s value function for older adults should reflect a steeper
curve near the origin for both gains and losses that reflects more feeling-based processing. This
modification to the parameters of Prospect Theory would predict that older adults would be more
risk seeking in losses and more risk averse in gains. Alternatively, if positive information only is
weighed more then only more risk aversion in gains would be predicted. If negative information
is gated out (and not experienced in order to maintain positive moods), then the shape of the
value function in the domain of losses should be more linear and less risk seeking in losses
compared to younger adults. We call these three alternatives an emotion bias, a positivity bias,
and a lack of negativity bias. Three relevant studies have been conducted and show inconsistent
age results. Lauriola and Levin (2001) found results consistent with an emotion bias.
Specifically, older adults demonstrated both greater risk aversion in gains and greater risk
seeking in losses. Weber et al. (2004) did a meta-analysis of decisions described to study
participants (no feedback was experienced) and found that increasing age (age ranges were not
specified in their paper) was associated with greater risk seeking (more choices of a gamble over
a sure thing) in losses; they did not, however, find a link between increasing age and risk
aversion (more choices of a sure thing over a gamble) in gains (suggesting no age-related
Peters and Västfjäll 19 Affective Processes in Decision Making
changes in the domain of gains). Holliday (1988), however, found no age differences from 20-76
years old in choices between gambles and sure things for gains or losses.
Loss aversion is also used to explain the “endowment effect”. In these studies, subjects
are either endowed with a good and asked the minimum amount for which they would sell it, or
they are asked the maximum amount for which they would be willing to buy it. Sellers tend to
require much more money than buyers are willing to pay (Thaler, 1980). The effect appears to be
larger when real money is involved, and it has been linked to affective processes (Peters, Slovic,
& Gregory, 2003; Lerner, Small, & Loewenstein, 2004). Older adults, if they generally rely
more on feelings, should exhibit a stronger endowment effect and their prices may be influenced
more by incidental affect such as moods. Kovalchik et al. (2005) found no endowment effect for
older or younger adults. Their methodology, however, appeared to maximize the amount of
deliberation in this task and therefore may have minimized the role of feelings that have been
found to be important to this effect (Peters et al., 2003). No other age-difference studies of the
endowment effect could be located.
These predictions can also be tested within the domain of framing effects in which the
same decision problem is “framed” or described in a positive or negative format. In a famous
example, McNeil, Pauker, Sox, and Tversky (1982) elicited different medical treatment choices
by describing the likelihood of the outcome in terms of survival (a positive frame) or mortality (a
negative frame). Presumably because 90% survival is less threatening than a 10% chance of
death, patients and experienced physicians chose the surgery option substantially more often in
the positive survival than the negative mortality frame.
If a general emotion bias is evident, then the negativity bias should be enhanced and older
adults should produce stronger framing effects relative to younger adults, leaving them more
vulnerable to possible manipulation through intentional or nonintentional framing. In support of
this interpretation, framing effects were larger for undergraduate participants low in deliberative
thinking (Smith & Levin, 1997). In addition, Bennett (2001) linked larger framing effects to the
addition of emotion-laden visual portrayals. Three studies concerning age differences in framing
effects showed opposing results with one finding that older adults demonstrated significantly
stronger framing effects while the other two found no age difference in the effect of frames (Kim
et al., in press; Mayhorn, Fisk, & Whittle, 2002; Rönnlund, Karlsson, Laggnäs, Larsson, &
Peters and Västfjäll 20 Affective Processes in Decision Making
Lindström, 2005). This issue deserves further attention. While the Rönnlund et al. study had a
small sample size (N = 32 per condition), sample sizes provided adequate power in the other two
studies, and opposing results were found nonetheless.
Time Preferences. Decisions made in the present have outcomes that occur in the future.
Several lines of research have hypothesized that time preferences change over the life span. For
instance, Trostel and Taylor (2001) suggested that the pleasure of consumption declines over the
lifespan, resulting in a devaluation of future experiences. In contrast, Sozou and Seymour (2003)
suggested that older adults may discount less than younger adults3 since they learned through
experience that the environment is safe enough to allow fewer immediate small rewards in favor
of distant larger gains. At the same time, Souzou and Seymour acknowledge that older adults'
time preferences may shift as health and perceived time decline. They suggest that the net effect
of these two processes over the life span is that discounting decreases until middle age after
which it increases markedly. This effect is consistent with SST in that it suggests that in old age,
when time is perceived as limited, short-term benefits become relatively more important (Lang &
Carstensen, 2002).
Read and Read (2004) found that older adults (75-89 years old) discounted more and
were less likely to choose a larger sum later and instead preferred a smaller sum sooner
compared to middle-aged and younger adults in tasks involving choices between monetary
outcomes. The effect was especially strong for outcomes with longer delays suggesting that as
people age they view the prospect of attaining pleasure from future consumption to be
increasingly less likely. A simpler explanation, though, is that they may perceive the likelihood
of cashing in later as lower due to shorter expected life span or shorter expected healthy life
span. If steeper discounts were shown by older adults for affective options over less affective
options, then we could say with more assurance that the effect was due to emotional goals. Tests
of these hypotheses are in process.
Time preferences may also be more directly related to the relative weight of affective
processes versus deliberative capacities. Temporal construal theory (Trope & Liberman, 2003)
suggests that temporal distance to the outcome influences how people construct mental
3 Discounting refers to how much less future money is worth now. If an individual discounts less, then they value future money relatively more and, thus, would show a relative preference for a larger later reward over a smaller immediate reward.
Peters and Västfjäll 21 Affective Processes in Decision Making
representations of the outcome. Distant outcomes are typically associated with more abstract,
simple and decontextualized representations, while near outcomes are represented by concrete,
complex and contextualized features. Thus, near outcomes are more likely to be affect-rich and
experiential (thus activating the experiential system/system 1) while distant outcomes may be
more affect poor and based on description (thus activating the deliberative system/system 2). We
are not aware, however, of any published studies that directly relate level of construal to age
differences in time preferences (but for a younger adult sample see Trope & Liberman, 2003).
Expected emotions and affective forecasting. Expected emotions concern predictions
about the emotional consequences of outcomes without any actual experience of emotion. In
decision making it is assumed that people predict the emotional outcomes of different
alternatives and act in order to maximize expected positive emotions and minimize expected
negative emotions (Loewenstein & Lerner, 2003). Affective forecasting can be defined as
“people’s predictions about how they will feel in a particular situation or toward a specific
stimulus” (Wilson & Klareen, 1992, p. 3). The anticipation of future happiness or sorrow is
assumed to be a motivator for efficient decision making. In agreement with this view, March
(1978) pointed out that all decisions concern predictions about future affect.
Research using younger adult populations has shown that people tend to overestimate the
intensity and duration of their feelings caused by a single event or outcome (they called this
effect an impact bias). For instance, Schkade and Kahneman (1998) found no differences in self-
reported well-being between students living in California and students living in the Midwest of
the United States. However, when the students were asked to rate the well-being of other
students living in different parts of the country, large differences were obtained. Californian
students believed that they would be less happy in the Midwest, and Midwest students predicted
that they would be happier living in California. A possible explanation for these findings is that
people focus on a single focal event failing to take into account other factors or non-focal events
that will contribute to, and ameliorate, their general well-being and feelings (Loewenstein &
Schkade, 1999).
Wilson, Gilbert and Salthouse (as cited in Wilson & Gilbert, 2003) asked to what extent
this impact bias may change over the life span. Wilson and Gilbert (2003) argued that it is
possible that the impact bias may be less pronounced with increasing experience and age. To test
Peters and Västfjäll 22 Affective Processes in Decision Making
this prediction, Wilson et al. asked a sample of participants aged 20-91 to rate how long it would
take to recover from an event (twelve different events ranging from a pleasant telephone chat to
death of a relative were used). They found a slight increase of duration between ages 20 to 60,
but at 60 a marked decrease in duration with increasing age was found (r = -.32). No age
differences existed between positive and negative events. Similar results were found when
looking at only one month (from the prediction), thus minimizing the possibility that expected
life span influenced the results. Wilson and Gilbert suggested that these results may be evidence
that older adults have learned that emotional events tend to dissipate quickly. If this is the case,
older adults will be more accurate than younger adults when future feelings are relevant to the
decision.
Affective forecasts may be based either on actual experiences (as in the example above)
or on cognitive derivations of the hypothesized affective impact of situations. In both situations,
imagining one’s reaction to changed circumstances is a key ingredient. Ligneu-Hervé and Mullet
(2005) found that perspective taking, the ability to take into account the point of view of another
person, was impaired among older adults. This suggests, however, that perspective taking in this
specific context was a highly cognitive task (considering relevant information and giving advice
to another individual).
Research on affective forecasts in younger adult populations has often focused on
specific emotions such as regret and disappointment that occur when the actual outcome is
compared to counterfactual outcomes (Zeelenberg et al., 1999). Since these emotions depend
crucially on cognitive processing (comparing information or alternative states of the world), it
may be predicted that such decision-related emotions (i.e. regret) are less prevalent in older adult
populations with declining deliberative capacities. While no research has tested this hypothesis,
other research has found that older and younger adults differ in what they regret (Jokisaari,
2004). In line with SST, older adults tended to report regrets associated with family and close
relationships, whereas younger adults regretted events linked to leisure time activities and
socially more distant relationships. Mather and Johnson (2003) also found that older adults
tended to attribute more positive and less negative attributes to a chosen alternative than younger
participants did. They suggest that such choice-supportive monitoring minimizes experienced
regret and maximizes satisfaction with the choice. Taken together, these studies suggest that
older and younger decision makers experience different decision-related emotions and perhaps
Peters and Västfjäll 23 Affective Processes in Decision Making
experience them in different domains of life (social decision vs. monetary decisions). This
hypothesis remains to be tested.
Complexity. Information complexity may impact decision making. Recent research by
Luce and colleagues (e.g., Luce, 1998) has shown that making trade-offs between important
decision attributes may impact choice through the elicitation of negative affect. For example,
Luce (1998) asked participants to choose one of four available automobiles. The choice task
required participants to make trade-offs between conflicting attributes. When the tradeoffs were
emotionally difficult (e.g., car A was better on Occupant Survival but worse on Pollution
Caused), participants reported experiencing stronger negative affect and chose the status-quo
option more than participants faced with low tradeoff difficulty (e.g., between Routine Handling
and Sound System). In another study, Drolet and Luce (2004) found that the impact of
emotionally difficult trade-offs on choice was minimized with cognitive load. The load
manipulation disrupted participants’ ability to consider self-relevant goal information and the
negative emotional consequences of making the trade off. Building on these findings, we predict
that age will influence the extent to which participants experience emotionally difficult trade-
offs. Older adults may experience relatively less trade-off difficulty with attributes due to
declines in deliberative capacity resulting in lesser negative affect and a greater tendency to
choose an alternative to the status quo.
Time Pressure. Dual-task paradigms such as time pressure manipulations have been
shown in younger adult populations to increase reliance on affective and heuristic processing of
information. For example, Shiv and Fedorikhin (2002) asked respondents to make a choice
between two snacks, chocolate cake (more favorable affect, less favorable cognitions) or fruit
salad (less favorable affect, more favorable cognitions) under time pressure. They found that
found that under high time pressure (and presumably less deliberative capacity) the chocolate
cake was selected significantly more than when time pressure was low. To the best of our
knowledge no studies have directly examined the impact of time pressure on older adult’s
decision making. However, Earles, Kersten, Mas, and Miccio (2004), showed that time pressure
significantly impacted memory recall among older adults. More important here is the finding that
during time-pressured cognitive tasks, older adults become anxious about their performance, and
they had trouble inhibiting negative self-evaluative thoughts about their performance.
Peters and Västfjäll 24 Affective Processes in Decision Making
Consequently, these process-generated or meta-cognitive experiences may hinder older adults’
performance in cognitive tasks including decision making.
Incidental Affect
A large body of research findings suggests that incidental affect (mood states, affective
primes, or conditioned responses that are normatively irrelevant to the decision) influences
people’s evaluations, judgments, motivation and information processing (for a review see
Forgas, 1995; Västfjäll, Peters, & Slovic, in preparation). Based on SST and DIT we predict that
incidental affect may particularly impact older adults’ judgments for two reasons; 1) incidental
mood states are more frequent, intense and salient among older adults (Lawton, 2001) and 2)
older adults may lack the capability of discounting or correcting for the influence of mood in
judgments and decisions, a cognitive process that younger adults are capable of performing
under normal conditions (Schwarz & Clore, 1983).
Priming. Hess, Waters, and Bolstad (2000) had different-aged adults make likeability
judgments about a series of Japanese Kanji characters. Presentation of each of these characters
was preceded by a positively or negatively valenced word that was presented either above or
below the participant’s perceptual threshold. Consistent with previous research by Murphy and
Zajonc (1993), likeability judgments tended to be consistent with the valence of the prime word
when participants were unaware of the prime word. In other words, individuals misattributed the
primed affective response to the Kanji characters when they were unaware of the source. In
contrast, when participants could consciously perceive the prime, only older adults exhibited
priming effects. A similar finding was obtained by Hess, McGee, Woodburn, and Bolstad (1998)
using a standard impression formation task. Two potential explanations for such effects are that
older adults are unable to control the impact of the primes on their judgments due to deficiencies
in deliberative processes or that older adults choose not to expend the effort necessary to control
for the impact of the primes. Another explanation, however, is that aging promotes an increased
focus on emotional information.
Mood. Decision makers look to both internal and external cues in a situation to help
them make decisions. How a decision maker feels about an option is one of the cues that is used
(Peters & Slovic, 1996; Peters et al., 2003). It is sometimes hard to distinguish, however,
between feelings for an object and currently salient feeling states such as moods. Although a
Peters and Västfjäll 25 Affective Processes in Decision Making
current mood state normatively should not impact longer-term decisions, these irrelevant sources
of emotional information have been shown to impact the judgments of younger adults (e.g.,
mood as information, Schwarz & Clore, 1983). When in a positive mood state, decision makers
will sometimes misattribute those feelings to judgments about unrelated objects and find the
object more attractive; in a negative mood state, decision makers again can misattribute those
feelings and find objects less attractive (e.g., Clore & Tamir, 2002; Sechrist, Swim, & Mark,
2003; Schwarz, 2001). Peters, Västfjäll, and Starmer (in review), for example, found that
younger adults paid more in real cash for a lottery ticket when induced to be in a positive versus
negative mood. This finding mirrors nonexperimental results of increases in stock prices on
sunny days when, presumably, buyer and seller moods are more positive (Hirshleifer &
Shumway, 2003). Older adults’ increased reliance on affective information may make them more
vulnerable to unrelated and irrelevant affective information (e.g., moods).
The effects of incidental affect, or irrelevant positive and negative mood states, on
judgment and decision processes have been little examined in older adults. Based on research
with younger adults and the finding that older adults tend to be in more positive and less negative
mood states relative to younger adults, several effects can be predicted. First, older adults should
demonstrate a mood-congruent effect, remembering more positive than negative information
relative to younger adults; this prediction is supported by research on Socioemotional Selectivity
Theory (e.g., Charles et al., 2003). Knight, Maines, and Robinson (2002), however, showed only
partial support of age differences in mood-congruency effects, with both younger and older
adults showing mood-congruency effects on some tasks and only older adults showing them on
other tasks. Ferraro, King, Ronning, Pekarski, and Risam (2003) found no age differences in
mood congruency although both younger and older adults showed the mood-congruency effect
(e.g., those individuals induced to feel happy responded faster to happy words than sad words).
The Ferrarro study, however, had several limitations including a small sample of older adults (N
= 25).
Second, older adults also might process information less systematically due to their
relatively more positive moods (Isen, 2000). Within the older adult group, higher levels of
negative affective states were associated with poorer memory. A recent study by Phillips, Smith
and Gilhooly (2002) showed that mood leads to greater executive function impairment in older
adults than it does in younger adults. Phillips et al. studied executive functioning through
Peters and Västfjäll 26 Affective Processes in Decision Making
planning in the Tower-of-London task (ToL: the task consists of moving discs to transform a
starting arrangement into a goal arrangement). Positive or negative mood was induced in both
younger and older adults through a combination of film and music. Following the mood
induction, participants completed the ToL task. A significant Age x Mood interaction was found
such that both negative and positive mood impaired performance for the older age group, while
mood had little effect on the younger adult group. The finding that both negative and positive
mood impaired performance was discussed in terms of three possible explanations: 1) mood may
act as a cognitive load, 2) positive mood may lead to impaired performance because positive
affect signals that goals have been achieved, thus reducing the motivation to engage in
systematic processing (Isen, 2000), and 3) emotion regulation: maintaining or attaining a positive
mood decreases the attention allocated to other cognitive activities. Finally, based on the
tendency for greater positive and less negative mood among older adults, older adults should be
more risk seeking in hypothetical decisions and risk averse in real decisions. We are not aware of
any published studies on this topic.
Depression and Anxiety. While positive affect and moods may be frequent and salient
among the elderly (Lawton, 2001), portions of this age group also suffer from various forms of
depression. The increasing prevalence of disability and institutionalization with age contributes
to the increase in depressive symptoms, but age-associated declines in dopaminergic and
noradrenergic reserves may also play a role (Fogel, 1991). Among younger adults, depression
and anxiety have been linked to biases in both judgment and information processing including
affect-congruent memories, depression biases in judgments of evaluative tasks, and risk
estimates (Ciarrochi, 1997; Keller et al., 2001; Gasper & Clore, 1998). Research on mood and
recall of autobiographical memory has shown that depressed older adults recalled more sad
memories than did older non-depressed adults (mood-congruent effect; Yang & Rehm, 1993). A
study by Deptula, Singh, and Pomara (1993) showed that older, but not younger adults,
consistently exhibited significant correlations between their performance on verbal recall
measures and their ratings of their anxiety, depression, and withdrawal. However, systematic
laboratory studies of decision making and depression or anxiety in older adults are largely
lacking. Several studies have linked depression to real behavioral outcomes (Blank et al., 2001;
Lee & Ganzini, 1992). For instance, Blank et al. (2001) found that depression was highly
associated with acceptance of physician-assisted suicide (PAS) and euthanasia in hypothetical
Peters and Västfjäll 27 Affective Processes in Decision Making
scenarios. Furthermore, compared with nondepressed people, depressed respondents were 13
times as likely to accept PAS when considering their current condition and over twice as likely to
accept PAS when facing a hypothetical terminal illness or coma. Depression alone was weakly
associated with life-sustaining treatment choices but, when impact of choices on personal
finances was made explicit, significantly more depressed subjects refused treatment options they
had previously desired than did nondepressed subjects.
Some recent research has investigated how specific incidental emotions impact
judgments and decisions in younger adults (Lerner & Keltner, 2001). For instance, Lerner et al.
(2004) found that the construction of prices (willingness to pay for a good) was impacted by the
mindsets of appraisal themes resulting from experimentally-induced incidental emotion states
(such as disgust and sadness). We expect that the impact of specific incidental emotions may
differ between age groups. Older adults tend both to have a richer palette of possible emotions
and to be more sensitive to emotional goals. As a result, we expect that the effects observed for
specific emotions in younger adults may be pronounced in an older age group. At the same time,
the more differentiated emotional life of older adults may lead to a sensation of mixed emotions
(Larsen, McGraw, Mellers, & Cacioppo, 2004). In one study, mixed integral emotions (anger
and fear) towards radiation sources led to a canceling of the cognitive appraisals that were
inconsistent across the emotions (Peters, Burraston, & Mertz, 2004). The prevalence and impact
of mixed appraisals needs further study in both younger and older adult populations.
Summary
Life-span theories can be interpreted as providing predictions about age differences in
judgment and decision making. Two life-span theories were reviewed (socioemotional
selectivity theory and dynamic integration theory). These theories predict that affective
information generally and positive information specifically will impact older-adult choices more
than those of younger adults. The theories offer different mechanistic explanations for these
changes (increases in emotional goals versus cognitive decline). We conducted a review of
published studies concerning the impact of affect and emotions in the decisions of older adults.
One of the main findings is that this literature is sparse and often offered opposing results.
Older adults, however, appear to learn affective information and make choices from
experience as well as younger adults despite cognitive declines; one study linked this to a more
Peters and Västfjäll 28 Affective Processes in Decision Making
accurate representation of gains and losses. No robust age differences existed with respect to
reactions to probabilities in decisions by description. Results of studies of choices between
gambles and sure things as well as framing effects showed mixed and therefore inconclusive
results. Older adults do appear to discount future monetary outcomes more although no studies
have yet been published on whether this tendency differs for affective versus less affective
stimuli. In many other potential areas for researching the impact of affective and emotional
processes on age differences in judgment and decision making, few, if any, published studies that
were directly related to the topic could be located. In general, less efficient judgment and
decision-making processes in older adults (compared to younger) may be evident mostly in
unfamiliar or meaningless situations devoid of affective significance to the decision maker.
Peters and Västfjäll 29 Affective Processes in Decision Making
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Affective resiliency – relative affective change
Age
Relative weight
in decisions
AffectiveprocessingDeliberativeprocessing
Affective enhancement – absolute affective change
Age
Relative weight
in decisions
AffectiveprocessingDeliberativeprocessing
Figure 1. Resiliency and enhancement in the weight of affective and deliberative
processing in decisions across the lifespan.
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